Strategy for Identifying a Robust Metabolomic Signature Reveals the Altered Lipid Metabolism in Pituitary Adenoma

作者全名："Tang, Jing; Mou, Minjie; Zheng, Xin; Yan, Jin; Pan, Ziqi; Zhang, Jinsong; Li, Bo; Yang, Qingxia; Wang, Yunxia; Zhang, Ying; Gao, Jianqing; Li, Song; Yang, Hui; Zhu, Feng"

作者地址："[Tang, Jing; Mou, Minjie; Pan, Ziqi; Zhang, Jinsong; Wang, Yunxia; Zhang, Ying; Gao, Jianqing; Zhu, Feng] Zhejiang Univ, Affiliated Hosp 2, Coll Pharmaceut Sci, Sch Med, Hangzhou 310058, Peoples R China; [Tang, Jing] Chongqing Med Univ, Dept Bioinformat, Chongqing 400016, Peoples R China; [Zheng, Xin; Yan, Jin; Li, Song; Yang, Hui] Army Med Univ, Xinqiao Hosp, Multidisciplinary Ctr Pituitary Adenoma Chongqing, Dept Neuosurgery, Chongqing 400037, Peoples R China; [Li, Bo; Yang, Qingxia] Chongqing Univ, Sch Pharmaceut Sci, Chongqing 401331, Peoples R China; [Zhu, Feng] Zhejiang Univ, Alibaba Zhejiang Univ Joint Res Ctr Future Digital, Innovat Inst Artificial Intelligence Med, Hangzhou 330110, Peoples R China"

通信作者："Zhu, F (通讯作者)，Zhejiang Univ, Affiliated Hosp 2, Coll Pharmaceut Sci, Sch Med, Hangzhou 310058, Peoples R China.; Li, S; Yang, H (通讯作者)，Army Med Univ, Xinqiao Hosp, Multidisciplinary Ctr Pituitary Adenoma Chongqing, Dept Neuosurgery, Chongqing 400037, Peoples R China.; Zhu, F (通讯作者)，Zhejiang Univ, Alibaba Zhejiang Univ Joint Res Ctr Future Digital, Innovat Inst Artificial Intelligence Med, Hangzhou 330110, Peoples R China."

来源：ANALYTICAL CHEMISTRY

ESI学科分类：CHEMISTRY

WOS号：WOS:001177964200001

JCR分区：Q1

影响因子：7.4

年份：2024

卷号：96

期号：12

开始页：4745

结束页：4755

文献类型：Article

关键词：　

摘要："Despite the well-established connection between systematic metabolic abnormalities and the pathophysiology of pituitary adenoma (PA), current metabolomic studies have reported an extremely limited number of metabolites associated with PA. Moreover, there was very little consistency in the identified metabolite signatures, resulting in a lack of robust metabolic biomarkers for the diagnosis and treatment of PA. Herein, we performed a global untargeted plasma metabolomic profiling on PA and identified a highly robust metabolomic signature based on a strategy. Specifically, this strategy is unique in (1) integrating repeated random sampling and a consensus evaluation-based feature selection algorithm and (2) evaluating the consistency of metabolomic signatures among different sample groups. This strategy demonstrated superior robustness and stronger discriminative ability compared with that of other feature selection methods including Student's t-test, partial least-squares-discriminant analysis, support vector machine recursive feature elimination, and random forest recursive feature elimination. More importantly, a highly robust metabolomic signature comprising 45 PA-specific differential metabolites was identified. Moreover, metabolite set enrichment analysis of these potential metabolic biomarkers revealed altered lipid metabolism in PA. In conclusion, our findings contribute to a better understanding of the metabolic changes in PA and may have implications for the development of diagnostic and therapeutic approaches targeting lipid metabolism in PA. We believe that the proposed strategy serves as a valuable tool for screening robust, discriminating metabolic features in the field of metabolomics."

基金机构："National Natural Science Foundation of China [82373790, 82301909, 22220102001, U1909208, 81872798, 81971982]; National Natural Science Foundation of China [LR21H300001]; Natural Science Foundation of Zhejiang Province [2022YFC3400501]; National Key R&D Program of China [181201*194232101]; Leading Talent of the ""Ten Thousand Plan"" National High-Level Talents Special Support Plan of China [2018QNA7023]; Fundamental Research Funds for Central Universities [2020C03010]; Key R&D Program of Zhejiang Province; Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare; Information Technology Center of Zhejiang University"

基金资助正文："This work was supported by the National Natural Science Foundation of China [82373790, 82301909, 22220102001, U1909208, 81872798, and 81971982]; the Natural Science Foundation of Zhejiang Province [LR21H300001]; the National Key R&D Program of China [2022YFC3400501]; the Leading Talent of the ""Ten Thousand Plan"" National High-Level Talents Special Support Plan of China; the Double Top-Class Universities [181201*194232101]; the Fundamental Research Funds for Central Universities [2018QNA7023]; the Key R&D Program of Zhejiang Province [2020C03010]; Westlake Laboratory (Westlake Laboratory of Life Science & Biomedicine); the Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare; Alibaba Cloud; and the Information Technology Center of Zhejiang University. Funding for open access charge: the Natural Science Foundation of Zhejiang Province [LR21H300001]."